1. Field of the Invention
The invention relates in general to cell simulation and in particular to a method and apparatus for modeling cellular structure and function which produces simulation data that is easily comparable to experimental data.
2. Prior Art
Tools such as fluorescent probes and confocal microscopy have enabled the resolution of three dimensional intracellular spatial distribution of different molecular species as well as sub-cellular structures. Research in cellular physiology requires the formation of theoretical hypotheses regarding the experimentally observed phenomena. These hypotheses are often formalized into mathematical models, and then tested by incorporating these models into simulations.
The deficiencies in existing technology originates from the current limitations of the cellular representation. Cells are represented as ideal and simple geometric shapes consisting of spatially homogeneous behavior (physiology) and structure (anatomy). This prevents the researcher from expressing an observed physiological phenomena in a simulation that maps easily to an actual experiment of an intact cell. Thus the validation of the model, and hence the hypothesis, is made very difficult.
Most current efforts in the modeling and simulation of cellular physiology are directed toward either very specific models of individual mechanisms or abstract representations of more complex phenomena. The specific models include models of individual molecular interactions such as ion channels gathered from biochemistry and electrophysiology research. The abstract models apply simplifications of the underlying mechanisms that are usually only appropriate to explain a small class of physiological problems.
Some typical abstractions include simplified simulation geometry, such as cable theory applied to nerve action potentials (where elementary features are uniform cross sections of nerve processes), or spatially homogenous grids with cell boundaries defined by geometric primitives (planes, spheres, cylinders). Additional abstractions include representing complex physiology in terms of a small number of variables with terms that try to approximate the overall effect of the underlying physiology (simple models of cellular signaling such as calcium dynamics).
Efforts to address the complexity of physiology also tend to concentrate on intercellular phenomena. The cellular automata approach looks at intercellular interactions where the fundamental computational unit represents an entire cell. There has also been numerous simulations in neuro-physiology involving models based on cable theory. These models decompose a single neuronal cell into computational elements representing entire cross sections of axons and dendrites. While these models reproduce the external behavior of action potentials in neurons with good fidelity, the inherent geometric simplicity of the formulation restrict their application to the class of problems where the cell interior can be considered a completely homogenous conductive media.
Interest has been shown in the collection of current physiological knowledge in a computer usable form. An example of this is SENEX, a computer based representation of cellular signal transduction processes in the central nervous system. This is an object oriented classification structure of biologic entities and significant relationships among them. However, their representation of biological entities and relationships are not in the form of actual mathematical models, and thus can not be used directly for simulations.
Present technology lacks good spatial correlation from simulation to empirical data. Typical simulations utilize an idealized geometry such as a cylinder, sphere, or plane rather than representing the geometry of an actual cell. The simulations are also spatially homogeneous, thus every part of the simulation has the same basic behavior, in contrast with actual cells. Thus, comparison of simulation with experiment is difficult or impossible.